Governmentality, counter‐conduct, and modes of governing: Accounting and the pursuit of municipal sustainable waste management
Bibliographic record
Abstract
Abstract Recent research into the uses of accounting as a technology of government has used Foucault's notion of “counter‐conduct” to shed light on various ways in which the governed can seek to alter the regimes to which they are subjected. This paper unpacks the notion of counter‐conduct further in order to develop a clearer conceptualization of how regimes of government can change over time, with or without clearly identifiable attempts by the governed to influence such changes. We develop our argument based on a longitudinal field study of sustainable waste management practices in a municipality in the English East Midlands. We track the municipality's attempts to become more sustainable in the context of an evolving central government performance management regime that went through a series of legislative and administrative iterations—namely, Best Value, Comprehensive Performance Assessment, and Comprehensive Area Assessment. We conceptualize these iterations of central performance management and the related changes in local government practices and technologies of governing as a series of overlapping “modes of governing” (Bulkeley et al., 2007, Environment and Planning A , 39 (11), 2733–2753). We suggest that accounting research can benefit from the notion of modes of governing because it sheds light on the theoretically expected, but empirically underresearched, copresence of multiple rationales, programs, and technologies of governing, all operating at the same time.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.009 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.003 | 0.021 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".